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Plant, space and time - linked together in an integrative and scalable data management system for phenomic approaches in agronomic field trials
BACKGROUND: To ensure further genetic gain, genomic approaches in plant breeding rely on precise phenotypic data, describing plant structure, function and performance. A more precise characterization of the environment will allow a better dealing with genotype-by-environment-by-management interactio...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7171732/ https://www.ncbi.nlm.nih.gov/pubmed/32336978 http://dx.doi.org/10.1186/s13007-020-00596-3 |
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author | Honecker, Andreas Schumann, Henrik Becirevic, Diana Klingbeil, Lasse Volland, Kai Forberig, Steffi Jansen, Marc Paulsen, Hinrich Kuhlmann, Heiner Léon, Jens |
author_facet | Honecker, Andreas Schumann, Henrik Becirevic, Diana Klingbeil, Lasse Volland, Kai Forberig, Steffi Jansen, Marc Paulsen, Hinrich Kuhlmann, Heiner Léon, Jens |
author_sort | Honecker, Andreas |
collection | PubMed |
description | BACKGROUND: To ensure further genetic gain, genomic approaches in plant breeding rely on precise phenotypic data, describing plant structure, function and performance. A more precise characterization of the environment will allow a better dealing with genotype-by-environment-by-management interactions. Therefore, space and time dependencies of the crop production processes have to be considered. The use of novel sensor technologies has drastically increased the amount and diversity of phenotypic data from agronomic field trials. Existing data management systems either do not consider space and time, are not customizable to individual needs such as field trial handling, or have restricted availability. Hence, we propose an integrative data management and information system (DMIS) for handling of traditional and novel sensor-based phenotypic, environmental and management data. The DMIS must be customizable, applicable and scalable from individual users to organizations. RESULTS: Key element of the system is a dynamic PostgreSQL database with GIS-extension, capable of importing, storing and managing all types of data including images. The database references every structural database object and measurement in a threefold approach with semantic, spatial and temporal reference. Timestamps and geo-coordinates allow automated linking of all data. Traits can be precisely defined individually or uploaded as predefined lists. Filtering and selection routines allow compilation of all data for visualization via tables, charts or maps and for export and external statistical analysis. New possibilities of environmental information-based planning of field trials, weather-guided phenotyping and data analysis for outlier or hot-spot detection are demonstrated. CONCLUSIONS: The DMIS supports users in handling experimental field trials with crop plants and modern phenotyping methods. It focuses on linking all space and time dependent processes of plant production. Weather, soil and management, as well as growth and yield formation of the plants can be depicted, thus allowing a more precise interpretation of the results in relation to environment and management. Breeders, extension specialists, official testing agencies and agricultural scientists are assisted in all steps of a typical workflow with planning, designing, conducting, controlling and analyzing field trials to generate new information for decision support in the crop improvement process. |
format | Online Article Text |
id | pubmed-7171732 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-71717322020-04-24 Plant, space and time - linked together in an integrative and scalable data management system for phenomic approaches in agronomic field trials Honecker, Andreas Schumann, Henrik Becirevic, Diana Klingbeil, Lasse Volland, Kai Forberig, Steffi Jansen, Marc Paulsen, Hinrich Kuhlmann, Heiner Léon, Jens Plant Methods Software BACKGROUND: To ensure further genetic gain, genomic approaches in plant breeding rely on precise phenotypic data, describing plant structure, function and performance. A more precise characterization of the environment will allow a better dealing with genotype-by-environment-by-management interactions. Therefore, space and time dependencies of the crop production processes have to be considered. The use of novel sensor technologies has drastically increased the amount and diversity of phenotypic data from agronomic field trials. Existing data management systems either do not consider space and time, are not customizable to individual needs such as field trial handling, or have restricted availability. Hence, we propose an integrative data management and information system (DMIS) for handling of traditional and novel sensor-based phenotypic, environmental and management data. The DMIS must be customizable, applicable and scalable from individual users to organizations. RESULTS: Key element of the system is a dynamic PostgreSQL database with GIS-extension, capable of importing, storing and managing all types of data including images. The database references every structural database object and measurement in a threefold approach with semantic, spatial and temporal reference. Timestamps and geo-coordinates allow automated linking of all data. Traits can be precisely defined individually or uploaded as predefined lists. Filtering and selection routines allow compilation of all data for visualization via tables, charts or maps and for export and external statistical analysis. New possibilities of environmental information-based planning of field trials, weather-guided phenotyping and data analysis for outlier or hot-spot detection are demonstrated. CONCLUSIONS: The DMIS supports users in handling experimental field trials with crop plants and modern phenotyping methods. It focuses on linking all space and time dependent processes of plant production. Weather, soil and management, as well as growth and yield formation of the plants can be depicted, thus allowing a more precise interpretation of the results in relation to environment and management. Breeders, extension specialists, official testing agencies and agricultural scientists are assisted in all steps of a typical workflow with planning, designing, conducting, controlling and analyzing field trials to generate new information for decision support in the crop improvement process. BioMed Central 2020-04-21 /pmc/articles/PMC7171732/ /pubmed/32336978 http://dx.doi.org/10.1186/s13007-020-00596-3 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Software Honecker, Andreas Schumann, Henrik Becirevic, Diana Klingbeil, Lasse Volland, Kai Forberig, Steffi Jansen, Marc Paulsen, Hinrich Kuhlmann, Heiner Léon, Jens Plant, space and time - linked together in an integrative and scalable data management system for phenomic approaches in agronomic field trials |
title | Plant, space and time - linked together in an integrative and scalable data management system for phenomic approaches in agronomic field trials |
title_full | Plant, space and time - linked together in an integrative and scalable data management system for phenomic approaches in agronomic field trials |
title_fullStr | Plant, space and time - linked together in an integrative and scalable data management system for phenomic approaches in agronomic field trials |
title_full_unstemmed | Plant, space and time - linked together in an integrative and scalable data management system for phenomic approaches in agronomic field trials |
title_short | Plant, space and time - linked together in an integrative and scalable data management system for phenomic approaches in agronomic field trials |
title_sort | plant, space and time - linked together in an integrative and scalable data management system for phenomic approaches in agronomic field trials |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7171732/ https://www.ncbi.nlm.nih.gov/pubmed/32336978 http://dx.doi.org/10.1186/s13007-020-00596-3 |
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